[Numpy-tickets] [NumPy] #932: Add new convolve method for faster computation of even functions

[NumPy]

#932: Add new convolve method for faster computation of even functions
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 Reporter:  xamusk       |       Owner:  somebody
     Type:  enhancement  |      Status:  new     
 Priority:  normal       |   Milestone:          
Component:  numpy.core   |     Version:  none    
 Severity:  normal       |    Keywords:          
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 Convolve and other functions which depend on convolve-like operations,
 like acorr, xcorr (those from matplotlib), etc, could use a new method to
 operate only on one side of the "full" mode.

 So, besides mode being "full", "same" and "valid", there could be a "half"
 mode (name only as a proposition) that could compute only one side of the
 function (lag>=0) so that it would return only len(x) elements instead of
 2*len(x)-1.

 This is particularly useful with the acorr function, for which a mode like
 that could compute the result much faster and represent only the wanted
 elements, much like Matlab's autocorr().

 Actual behavior in matlab: autocorr(x)[[BR]]
 What is currently needed to do in numpy/pylab:[[BR]]
 a=acorr(x-x.mean(),normed=True)[1][len(x)-1:][[BR]]
 close()[[BR]]
 plot(a,marker='.')[[BR]]
 #And that doesn't count doing fancy markings in the plot like the matlab
 ones.

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Ticket URL: <http://scipy.org/scipy/numpy/ticket/932>
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